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Enhancement of Automotive Diagnostic Tool for Efficient Bus Troubleshooting
  1. case
  2. Enhancement of Automotive Diagnostic Tool for Efficient Bus Troubleshooting

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Enhancement of Automotive Diagnostic Tool for Efficient Bus Troubleshooting

sigma.software
Automotive
Manufacturing

Challenges in Existing Diagnostic Tool

Inefficient fault diagnosis processes in bus electrical systems due to information overload, lack of user-friendly interface, and absence of real-time feedback mechanisms. Existing tools displayed excessive technical data, complicating repair decisions for technicians.

About the Client

A premium class truck manufacturer with global presence, providing reliable and highly efficient customer support and repair services

Key Project Goals

  • Improve diagnostic efficiency through simplified interface design
  • Implement advanced search and caching capabilities
  • Optimize code and database performance
  • Enable real-time feedback integration
  • Reduce technician decision-making time

Core System Enhancements

  • Contextual fault code prioritization with expandable details
  • Advanced search and local caching mechanism
  • Modular codebase architecture with optimized SQL queries
  • Integrated technician feedback submission system
  • Progressive information disclosure interface

Technology Stack

C#
.NET Framework
SQL Server
WPF

System Integrations

  • Vehicle diagnostic hardware interface
  • Scania's existing repair database
  • Customer feedback management system

Quality Attributes

  • Sub-second response time for critical operations
  • 99.9% system availability
  • Role-based access control
  • Cross-platform compatibility with diagnostic hardware
  • Scalable architecture for global deployment

Expected Business Outcomes

Anticipated 30-40% reduction in diagnostic time through streamlined interface, 25% improvement in technician productivity via efficient search capabilities, and enhanced service quality through real-time feedback implementation. System optimization expected to reduce maintenance costs by 20%.

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